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The COoKIE Group

Communication, Organization of Knowledge, Information Ecosystems 

What we Do

The COoKIE is an interdisciplinary Human-Computer Interaction research group focusing on Human-AI collaborative communication.

Our recent work touches on diverse technologies, including conversational agents, large language models, generative AI systems, and AI-based decision support systems. Seeking to advance Human-AI interaction design, we explore mechanisms driving the perceptions of different types of AI systems, such as trust, anthropomorphization, or perceived reliability to inform the system and algorithm design requirements for effective, efficient, and ethical AI.

Our Work is Supported by:

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The Natural Sciences and Engineering Research Council of Canada (NSERC)

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The Social Sciences and Humanities Research Council of Canada (SSHRC)

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The Naver Corporation,

South Korea

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The Faculty of Information,

University of Toronto, Canada

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Data Sciences Institute,

University of Toronto, Canada

Current Research Areas

Human-Agent Communication

The growing complexity of intelligent systems creates a promising environment for the shift in a user experience paradigm: from pure human-system interaction to human-system communication and collaboration. This is further amplified by the increased popularity of entity-based system interfaces (artificial agents) and the integration of conversational user interfaces (CUI). The human-agent communication paradigm opens exciting opportunities to exploit a computer's unique abilities to complement humans. However, first, we need to understand the specifics of human-agent communication.

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AI-Based Decision Support Systems (ADS)

AI-integrated decision-making support systems allow to augment and extend human capabilities, improving the quality and efficiency of decisions. These systems use AI to learn, remember, analyze, and reason based on large amounts of often complex data. The successful use of these features requires an understanding of how they can appropriately complement human processes. To address these questions, we explore what aspects of augmentation are required in different scenarios, how the outcomes should be communicated and explained (xAI), and how to properly calibrate and, if needed, repair trust in systems' performance. 

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Information Architecture for Conversational UI

The intuitive nature of Conversational User Interfaces (CUI), fashioned after natural human conversation, allows for convenient and fast input and can serve as a single-channel input for multiple services, devices, applications, and even environments. However, due to the absence of visual clues, affordances, and spatial organization, the use of CUI is associated with a decreased sense of control over the information dynamics. We explore the perceived “locations”, “structure“, and “paths” of the information shared through CUI, to inform the required information architecture. 

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Meet the Team

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Anastasia Kuzminykh

Assistant Professor, 

iSchool, cross-ap. w. Computer Science, University of Toronto

Head of The COoKIE Group and the THAI RS

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Manveer Kalirai

Ph.D. Student,

Prev. Master's Thesis Student,

Faculty of Information, 

University of Toronto

Conversational Recommender Systems

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Fatima Zohra

Master's Thesis Student,

Faculty of Information, 

University of Toronto

Bias Mitigation Techniques for ML Models

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Yuxin Xu

External Research Assistant,

Prev. Master's Thesis Student, Faculty of Information, 

University of Toronto

Sense of Ownership in Human-AI Collaboration

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Huayin Luo

Undergraduate

Research Assistant, 

Statistics and Computer Science, University of Toronto

Backhanneling in Human-AI Communication

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Pelin Tanberg

Postdoctoral Fellow,

Faculty of Information, 

University of Toronto

Memory Retention in Human-AI Communication

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Paula Aoyagui

Ph.D Student, 

Prev. Research Assistant, 

Faculty of Information, 

University of Toronto

Argumentative Strategies in Verbal Explainable AI

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Anshuta Kulkarni

Master's Thesis Student,

Faculty of Information, 

University of Toronto

Social Dynamics in Human-AI Communication

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Justice Cheng

Master's Research Assistant, 

Applied Psychology & Human Development at OISE,

University of Toronto

Operationalizing the Sense of Digital Ownership

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Rimsha Rizvi

Lab Coordinator, Research Assist., Prev. Reading Student,

iSchool, University of Toronto

Fairness and Explainability in Human-AI Collaboration

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Senjuti Dutta

Ph.D. Student,

Electrical Eng. & Computer Science, University of Tennessee, Knoxville

Intelligent Systems for Crowdwork Flexibility

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Janet Lu

Master's Thesis Student,

Faculty of Information, 

University of Toronto

Conversational Agents for Co-Design Assistance

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Nazar Ponochevnyi

External Research Assistant,

Prev. Mitacs Research Intern, Faculty of Information, 

University of Toronto

Developing Voice Interface for Data Visualization

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Christina Wei

Ph.D. Student,

Faculty of Information, 

University of Toronto

Conversation Architecture for Human-AI Communication

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Harsh Kumar

Ph.D. Research Assistant,

Computer Science,

University of Toronto

Cognitive and Behaviour Impact of Human-AI Communication

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Omer Imran

Master's Research Assistant,

Faculty of Information, 

University of Toronto

Subjectivity of Financial Fairness in Explainable AI

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Shradha Anand

External Research Assistant,

Prev. Reading Student, 

Faculty of Information, 

University of Toronto

Document Exploration with Conversational Interfaces

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Rezvan Boostani

Ph.D. Student,

Faculty of Information, 

University of Toronto

Agents for Financial Assistants for Older Adults

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Sharon Ferguson

Ph.D Research Assistant, 

Mech.and Industrial Eng., University of Toronto

AI Explanations in 

Collaborative Non-Ground-Truth Decision-Making

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Janna Cameron

Master's Research Assistant,

Faculty of Information, 

University of Toronto

Types of Trust in Human-AI Collaboration

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Emily Su

Undergraduate

Research Assistant, 

Statistics and Computer Science, University of Toronto

Conversation in Human-AI Communication

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Omid Veisi

Ph.D Student, 

Faculty of Information, 

University of Toronto

Humanized AI in Human-AI Collaboration

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Dr. Angeline Tsui

External Research Assistant,

Faculty of Information, 

University of Toronto

The Effects of AI Explainability on Human-AI Collaboration

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Dakshata Shukla

Master's Research Assistant, 

Faculty of Information, 

University of Toronto

Agents For Female Health in Developing Regions

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Annie Tan

Undergraduate

Research Assistant, 

Computer Science,

University of Toronto

Verbal Explanations in Human-AI Communication

Team

Alumni

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Yaqing Yang

Mitacs Globalink Research Intern, 2023, Faculty of Information, UofT

Cross-Modality Alignment of Prompts for Art Generation

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Hidaya Ismail

Research Assistant,

Faculty of Information, UofT

Psychological Ownership in Human-AI Collaboration

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Mujgan Ozceylan

Master's Research Assistant, Reading Student, THAI RS'21

Faculty of Information, UofT

AI Explanations of Subtle Sexism

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Nabila Chowdhury

PhD Research Assistant, 

THAI RS'22, Faculty of Information, UofT

Promt-Based Bias in AI Generated Art

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Juan Antonio Nelson

Research Assistant,

Faculty of Information, UofT

Speech Detection of Caribbean Dialects

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Yihui Lu

Mitacs Globalink Research Intern, 2023, Faculty of Information, UofT

Conversational Agents for Psychological Therapy

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Deepak Surya

Mitacs Globalink Intern, 2022, Faculty of Information, UofT. Text-to-Voice Conversation Style Transformation

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Ashvanth Rathinavel

Mitacs Globalink Research Intern, 2023, Faculty of Information, UofT

The Role of Modality in Human-AI Conversation

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Kusum Grandhi

Mitacs Globalink Research, 2022, Faculty of Information, UofT. Modality-Dependant Decision Effects of AI Explanations

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Olha Liuba

Research Intern, 2023, 

Faculty of Information, UofT

Supporting Equal Participation in Group Discussions

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Kelly McConvey

Ph.D. Research Assistant,

Faculty of Information, UofT

Collaboration with AI Models in Education

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Marianna Kovalova

Research Intern, 2023, 

Faculty of Information, UofT

The Effects of Explanation Format on The Perceived Trustworthiness

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Bill Than

NSERC USRA, BI student,

Faculty of Information, UofT

Engagement in Teleconferencing Classrooms During Covid-19

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M. Elkhechen

Research Assistant,

Faculty of Information, UofT

Psychological Ownership in Human-AI Collaboration

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Mona Abou Swaid

Master's Research Assistant,

Faculty of Information, UofT

Sense of Ownership Over Digital Artifacts

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Tanisha Amarakoon

Research Assistant,

Faculty of Information, UofT

Psychological Ownership in Human-AI Collaboration

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Akriti Kaur

Master's Research Assistant,

Faculty of Information, UofT

Document Exploration Through Conversational Interfaces

Past Reading/Research Course Students:

Dakshata Shukla - Master's Reading Student, Faculty of Information, UofT. Health Agents For Women in Global South | S,F2023

Janna Cameron - Master's Reading Student, Faculty of Information, UofT. Types of Trust in Human-AI Collaboration | S,F2023

Omer Imran - Master's Reading Student, Faculty of Information, UofT. Bias Mitigation Techniques in ML | S,F2023

Amy WangMaster's Reading Student, Faculty of Information, UofT. Attention Support Through Conversational Agent | S,F2023

Rimsha RizviMaster's Reading Student, Faculty of Information, UofTFairness and Explainability in Human-AI Collaboration | S2023

Fatima Zohra Master's Reading Student, Faculty of Information, UofT. Accuracy Preserving Fairness Techniques for Financial Models| S2023

Anshuta Kulkarni Master's Reading Student, Faculty of Information, UofT. Social Dynamics in Human-Agent Interaction | S2023

Janet Lu - Master's Reading Student, Faculty of Information, UofT. Conversational Agents for Co-Design Assistance | S2023

Kshitij AnandMaster's Reading Student, Faculty of Information, UofTConversation in Human-AI Collaborative Tasks | S2023

Batool Fatima - Master's Reading Student, Faculty of Information, UofT. Trust Mechanisms in Human-AI Collaboration | S2023

Lakshya - Master's Reading Student, Faculty of Information, UofT. Designing Human-AI Conversation | S2022

Mohammed Elkhechen - Master's Reading Student, Faculty of Information, UofTHuman-AI Teams | S2022

Lakshya - Master's Reading Student, Faculty of Information, UofT.  Designing Human-AI Conversation | S2022

Shradha AnandMaster's Reading Student, Faculty of Information, UofTExploration of Documents Through Conversational Interfaces | S2022

Jinchi Lin - Master's Reading Student, Faculty of Information, UofT. Personalization of Disembodied Intelligent Agents | S2022

Lizhen Ying - Master's Reading Student, Faculty of Information, UofT. Anthropomorphization of Disembodied Agents | W2022

Paula Akemi - Master's Reading Student, Faculty of Information, UofT. Designing Technology for Older Adults | F2021

Manveer Kalirai - Master's Reading Student, Faculty of Information, UofT. The Adoption of Smart Home Technology in Everyday Use | S2021

Julia Gil Undergrad Reading Student, Faculty of Information, UofT. User Communication with Conversational Agents | S2021

Ruijia Yang Undergrad Reading Student, Computer Science, UofT. Simulation As a Research Method in HCI | W2021

Join the Team

PostDocs 

We would be happy to consider applications from potential postdoc candidates. Typically, a postdoc contract is offered for a year with a potential consequent extension for another year. Currently, we are looking for postdoc candidates, broadly interested in Human-AI Collaboration with a particular focus on conversational interactions. If you are interested in a postdoc in our group, please send your CV, writing samples, and a brief statement of research interest to Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca).

Ph.D. Program 

We invite applications from candidates with a Master's degree in Computer Science, Systems Design Engineering, Data Science, Psychology, Communication Studies, or similar fields. Research experience is expected, academic publications are a plus. The application period is typically open September-November, with entry into the program once a year, in September. Please review the admission requirements to the Ph.D. in Information. It is highly recommended to contact your potential supervisor and have a discussion about your research plans and interests. If you are interested in a Ph.D. in our group, please send your CV, writing samples, and a brief statement of research interest to Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca).

Master's Thesis

The Master's Thesis option at the COoKIE group is available to students, enrolled in the Master's of Information program at the iSchool, University of Toronto. Please review the pre-requisites and eligibility for the master's thesis. To inquire about the reading course and/or the thesis work at the COoKIE Group, please send your CV and a brief statement of research interest to Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca). If applicable, please mention any relevant experience, including prior research experience and/or reading courses taken in the past.

RAship

In most of the academic terms (September-December, January-April, May-August), the COoKIE Group has 1-2 Research Assistantship positions available for Master's or undergraduate level students. While typically we hire students from the University of Toronto, external applications can occasionally be considered. The standard RA contract in our group includes 12 weeks, 5-6 hours per week, working on an individual or a group project. To inquire about open positions and to apply for RAship, please contact Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca) no later than a week before the beginning of an academic term. Please include your CV and a brief statement of research interest.

Our Collaborators

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